The 31-year-old No 8 cum second row has long been obscured by likes of Dominguez and Bergamasco.
The R 2 (cum) and Q 2 (cum) are the two parameters that describe the goodness of the models.
Model Runtime (min) Average operating temperature (°C) Cum. oil produced (cm3) Cum.
The incremental cost-effectiveness ratio was defined as ICER : = C ̄ DSQ < 4 Cum - C ̄ DSQ ≥ 4 Cum Ē DSQ < 4 AUC - Ē DSQ ≥ 4 AUC, (5).
Therefore, the supervised OPLS-DA analysis gave a good model [1 + 2 + 0, R 2 X (cum) = 0.725, R 2 Y (cum) = 0.728 and Q 2 (cum) = 0.53] with a clear partition between DENTAMET® treated and untreated samples (Fig. 4a).
The Bayesian method was applied to calculate the posterior predictive differences of effectiveness means Ē DSQ < 4 AUC - Ē DSQ ≥ 4 AUC and cost means C ̄ DSQ < 4 Cum - C ̄ DSQ ≥ 4 Cum.
This case has been considered in [20], where it has been shown that ∀ i ∈ { 1, …, 4 }, Cum s i, s i, s i, s i = - 2, Cum s 1, s 2, s 3, s 4 = 1 (8).
The unsupervised method (PCA) gave unclear results (see Additional file 1: Figure S3), while the OPLS-DA analysis gave a good model [1 + 2 + 0, R 2 X (cum) = 0.786, R 2 Y (cum) = 0.837 and Q 2 (cum) = 0.489], showing a clear partition between DENTAMET® treated and untreated samples along the first predictive component (Fig. 5a).
PCA (a) t[1]/t[2] and (b) t[2]/t[4] score plots for Cellina di Nardò cultivars, considering DENTAMET® treated and the untreated samples [six components, R 2 X (cum) = 0.935, Q 2 (cum) = 0.816].
To estimate the fourth-order cumulant of X, we can derive an estimator from the Leonov-Shiryayev formula (8): Cum 4 ̂ X = μ 4 ̂ - 3 μ 2 ̂ 2. (12..
The explorative unsupervised method (PCA) used for the whole data did not give clear group separation (data not shown), while the OPLS-DA model based on treated vs. untreated category as discriminating class (Fig. 3) produced a good descriptive but weak predictive model [one predictive and four orthogonal components give R 2 X (cum) = 0.82, R 2 Y (cum) = 0.60, and Q 2 (cum) = 0.24].
